{"_buckets": {"deposit": "522a0fa8-39e2-4d7f-8ef6-016f46ae2791"}, "_deposit": {"created_by": 2, "id": "1233", "owners": [2], "pid": {"revision_id": 0, "type": "depid", "value": "1233"}, "status": "published"}, "_oai": {"id": "oai:kutarr.kochi-tech.ac.jp:00001233", "sets": ["25"]}, "author_link": ["3309", "3307", "3308", "3306"], "item_5_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2014-12", "bibliographicIssueDateType": "Issued"}, "bibliographicVolumeNumber": "9", "bibliographic_titles": [{"bibliographic_title": "Society for Social Management Systems Internet Journal"}]}]}, "item_5_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "Climate change is widely recognized to have an adverse effect on both short and long-term,\nespecially under uncertainty of water resource availability. Water is not only affecting drinking and food\navailability, but also services and industrial manufacturing departments those are significant to our\neveryday-life. To retain water resource service under such an uncertainty and economics recession\ncircumstance, governor has to determine an appropriate policy from a single or a combination of multiple\ndemand-reduction and supply-increment options, which is not an easy task for the governor.\nThis paper describes designing of a system to answer the best water resource policy under a given\nconstraint conditions, e.g. cost, ease to implement, social and economic scenario, etc. A final solution is\ndetermined from considering a vast of number of scenarios from all possible options combinations and\nuncertainty from climate change prediction, and give the best scenario back to governor in real-time. In each\nscenario, water resource equilibrium from predicted demand and supply in future is calculated, based on a\ngiven (generated) policy, economic and social effects on water shortage are determined.\nA modern GPU computing and cloud computing technology are integrated in order to serve the most\nconvenient experience to the system users. Adopting GTX-Titan GPU, the system could serve about 1,600,000\nscenarios per minute, which is about several ten thousand times faster than the previous system framework.\nThis enable governors using the system to make a decision on the fly.", "subitem_description_type": "Abstract"}]}, "item_5_publisher_36": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "Society for Social Management Systems"}]}, "item_5_version_type_19": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_970fb48d4fbd8a85", "subitem_version_type": "VoR"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "BONGOCHGETSAKUL, Nattakorn"}], "nameIdentifiers": [{"nameIdentifier": "3306", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "SUTTINON, Pongsak"}], "nameIdentifiers": [{"nameIdentifier": "3307", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "UEMOTO, Kotomi"}], "nameIdentifiers": [{"nameIdentifier": "3308", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "NASU, Seigo"}], "nameIdentifiers": [{"nameIdentifier": "3309", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2019-02-13"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "sms13-3681.pdf", "filesize": [{"value": "267.8 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 267800.0, "url": {"label": "sms13-3681.pdf", "url": "https://kutarr.kochi-tech.ac.jp/record/1233/files/sms13-3681.pdf"}, "version_id": "e2f47ab1-a01a-4a4a-adc5-551fcf4713a7"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "conference paper", "resourceuri": "http://purl.org/coar/resource_type/c_5794"}]}, "item_title": "Real-Time Water Resource Policies Supporting System for Decision-Making Based On GPU Application", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Real-Time Water Resource Policies Supporting System for Decision-Making Based On GPU Application"}]}, "item_type_id": "5", "owner": "2", "path": ["25"], "permalink_uri": "http://hdl.handle.net/10173/1236", "pubdate": {"attribute_name": "公開日", "attribute_value": "2015-02-28"}, "publish_date": "2015-02-28", "publish_status": "0", "recid": "1233", "relation": {}, "relation_version_is_last": true, "title": ["Real-Time Water Resource Policies Supporting System for Decision-Making Based On GPU Application"], "weko_shared_id": -1}